ake a network of lines (i.e. a graph) and make a Plankton Mesh, from which you can use Cytoskeleton to make a solid mesh (and then smooth it with Weaverbird).
Works with ngons (polygons with 3 or more sides). Other examples I found only worked with tris and quads.
Works on open or closed surfaces
While these examples start with a surface, you could start with a network of lines and make a patch surface
This is meant for 2D networks/surfaces. I haven't attempted filling a 3D volume. My guess is this wouldn't work as it would require a non-manifold mesh that Plankton wouldn't handle.
Note similar results could be achieved with the following:
TSplines
MeshDual (dual of a tri mesh, not as much freedom/control)
Working backwards, here is the GhPython script from Will Pearson that builds a Plankton Mesh from vertices and faces. The vertices are a list of 3D coordinates, the faces are a tree a lists, with each list containing the indices of vertices that form a closed loop. From Will, "Plankton only handles manifold meshes, i.e. meshes which have a front and a back. This orientation is determined by the "right-hand rule" i.e. if the vertices of a face are ordered counter-clockwise then the face normal will be out of the page/screen."
# V: list of Point3d # F: tree of int
import Grasshopper appdata = Grasshopper.Folders.DefaultAssemblyFolder
import clr clr.AddReferenceToFileAndPath(appdata + "Plankton.dll")
import Plankton
pmesh = Plankton.PlanktonMesh()
for pt in V: pmesh.Vertices.Add(pt.X, pt.Y, pt.Z)
for face in F.Branches: face = list(face)[:-1] pmesh.Faces.AddFace(face)
These vertices and faces are precisely the output from Starling. Starling takes in a list of Polylines which form the (properly oriented) face loops.
The polyline face loops can be generated...
Directly from Panels on a surface using LunchBox
Using any network of lines/curves on a surface (curves will need to be converted to polylines before Starling)
The latter was achieved using the Surface Split command, then converting the face edges (converted to curves) into polyline loops to represent faces.
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requires four weather data inputs: air temperature (_dryBulbTemperature), relative humidity (relativeHumidity_), wind speed at 1.1 meters from the ground (windSpeed_) and mean radiant temperature (meanRadiantTemperature_).You can add values to the first three inputs from the Ladybug "Import Epw" component. For the last (meanRadiantTemperature_), you can add it from Ladybug's "Outdoor Solar Adjusted Temperature Calculator" component, or let "Thermal Comfort Index" component to calculate it. Both use different methods to calculate the final values.
I attached an example file below with second option.For more precise calculations you can use Honeybee and Chris' microclimate maps.An icing on the cake for the end: one of Ladybug developers yesterday released a set of Ladybug components for modelling in ENVI-met application. ENVI-met is cutting-edge microclimate software, which can be downloaded for free. It opens a number of advanced new analysis in outdoor domain, which couldn't have been done with the current Ladybug+Honeybee tools. So you can perform the simulation in ENVI-met 4 free software, and then add mean radiant temperature values from ENVI-met simulation to "Thermal Comfort Indices" component. Here is an example file.If you would like to go with the last approach, then the best would be to post a question about it in this topic.
1) You can make a polygonized tree.I haven't subtracted the trunk from the crown, but I guess it makes sense that it can be done.2) In most solar related simulations, a default albedo value of 0.2 is used. This corresponds to average albedo value taken from materials surrounding the urban or countryside location (concrete, grass, gravel, sand, asphalt...). However the presence of snow can significantly magnify the average albedo value several times. "Sunpath shading" components albedo_ input has an ability to calculate albedo due to presence of snow, if nothing is added to it (to albedo_ input). As you are performing the analysis of PET in a horizontal plane, it will not affect your calculations.3) Most thermal comfort indices will require performing analysis at 1.1 meters above the ground. This is considered to be height of standing person's gravity center.The same goes for PET index. So you are correct: you should place the analysis grid at 1.1 meters above the ground before adding it to the "Sunpath Shading" component.It is worth mentioning that "Thermal Comfort Indices" component used in this topic's PET_on_Grid2.gh and PET_on_Grid3.gh files is from last year, and much slower than the newest one (VER 0.0.64 MAR 18 2017) used in the example attached below. Just a remainder if you have been using older version of this component.Let me know if I misunderstood some of your questions, or if I missed to answer some of them.
EDIT: sorry for posting a double reply. When I posted it the first time, I only got links visible, with no text. Something has been wrong with grasshopper ning forum for the last couple of months.…
). It deals with the potential possibility to port GH into AEC fields (real-life AEC fields, nothing to do with academic thinking). The bad news are that the smart AEC sector is occupied solely by Bentley/GenComp – expect soon Revit/Dynamo as well (not to mention CATIA). The good news are that there’s millions of designers/engineers/industrial designers out there who could be interested for a 3rd alternative.
Intro: Well, in the old days (when men had mustache and muttonchops) AEC design performed in a nice top-to-bottom sequence (kinda like a vector) : the Big Man (aka The Brain) did some sketches (with crayons) and the rest (known as the “others”) struggled to make The Idea a reality. Today things are different, mind. Or they should be different. Or may be different. Or whatever. The big easy:For a zillion o reasons (AEC matures, PLM, cost, outsourcing, sustainable engineering…add several more) this vector like process of the past is like a Brown motion these days: Right down the moment that you (or your team) “sketch” The Big Idea … another team design simultaneously (i.e. in parallel) the components (parts) that compose the whole. This is the so called bottom-to-top design mentality. So the whole and the parts meet in some "middle point" instead the later being dictated by the former. In quite a few occasions parts dictate the whole (cost, cost and cost being the main reasons). The more a design is contemporary the more this bottom-to-top thing plays a critical role. Ignore it and have a very big time (sooner or later).The bad news:If you accept the above…well GH – at present phase - is not ready for contemporary AEC work. At.All.3 Main reasons for that:1.You can’t use parametric parts (i.e. nested blocks to speak Rhino language) into a given definition (in this case attached : truss nodes, connection flanges, mount plates, cable tensioners, planar glazing components, roof skin components…etc etc). This is obviously a Rhino domain.2.You can’t bake a given solution in such a way that the Rhino file is structured (i.e. assemblies of nested blocks). Or you can do it theoretically writing some VB/C code – but the core of the matter is that corresponding components are MIA. That means that you can’t export anything useful actually into established AEC oriented apps and/or established MCAD apps (for doing/calculating the parts for real-life production).3.The GH process can’t being interrupted. Imagine defining, say, a building “envelope” in GH and then …er…use Evolute tools in order to optimize things (say quad planarization and the likes). Then …continue in GH for more detailed work. Then design the parts as in 1 above. Then back to Evolute. Then back to GH.So…if anyone is interested I would be glad to start the mother of all debates and/or some kind of crusade (GH for President, that is).PS: This definition is a WIP thing – more refined stuff to follow (in particular a complex canopy tubes pre-stress system).
PS: Tree8 components are used sporadically.
PS: Use Saved Views
May the Dark Force be with us.Best, Peter …
. From the Thermal Comfort Indices component, Comfort Index 11 (TCI-11):MRT = f(Ta, Tground, Rprim, e)
with:- Ta = DryBulbTemperature coming from ImportEPW component- Tground = f(Ta, N) where N comes from totalSkyCover input. Tground influences the long-wave radiation emitted by the ground in the MRT calculation.- Rprim defined as solar radiation absorbed by nude man = f(Kglob, hS1, ac)- ac is the clothingAlbedo in % (bodyCharacteristics input)- I can't find any definition in the code of Kglob and hS1. Could you tell me please what are those values referencered to? --> probably the globalHorizontalRadiation but how?- e = vapour pressure calculated from Ta and Relative Humidity input
Do you agree that in this case the MRT does not depend on these inputs: location, meanRadiantTemperature, dewPointTemperature and wind speed?It does not depend neither on the other bodyCharacteristics like bodyPosture, age, sex, met, activityDuration...?
MRT calculated by the TCI-11 method is the mean radiant temperature of a vector pointing vertically with a sky view factor of 100%?For ParisOrly epw,
2. From the SolarAdjustedTemperature component (that seems to be more used for the UTCI calculation examples on Hydra compared to TCI-11).
In contrast to the TCI-11, this component distinguishes diffuse and direct radiation and contextualizes the calculation thanks to _ContextShading input, right? It can also be applied to a mannequin thanks to the CumSkyMatrix and thus evaluate the dishomogeneity of radiation exposure.This component seems not to consider the influence of vapour pressure on the result --> is it then more precise to put the MRT output (from the TCI) as an input of meanRadTemperature for SolarAdjustedTemperature?The default groundReflectivity is set to 0.25 --> is GroundReflectivity taken into account in the Tground or MRT calculation in the TCI component? If yes, what is the hypothesised groundReflectivity?The default clothing albedo of 37% (TCI-11 bodyCharacteristics) corresponds to Clothing Absorptivity of 63%?
If the CumSkyMatrix input is not supplied, I get 9 results for the mannequin --> where are those points/results coming from?
If the CumSkyMatrix input is supplied,I suppose the calculation of the 482 results correspond to a calculation method similar to the radiation analysis component that is averaged over the analysis period. Right?But I don't understand why the mannequin is composed of 481 faces and meshFaceResult gives 482 results.
Finally, what is the link between the MESH results, the solarAdjustedMRT and the Effective Radiant field ? Is there a paper to have a detailed explanation of the method?
3. Here are some results for the ParisOrly energyplus weather data. You can find here attached the grasshopper definition.There is no shading in this simulation and the result coming from the ThermalComfort indices for MRT is very different compared to the solar adjusted MRT.Why such a big difference and which of the result should be plugged into the UTCI calculation component?
Results for ParisOrly.epwM,D,H:1,1,12
Ta : 6.5°Crh: 100%globalHorizontalRadiation: 54 Wh/m2totalSkyCover: 10MRT (TCI-11): 1.2°C
_CumSkyMtxOrDirNormRad = directNormalRadiation : 0 Wh/m2diffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.64°CMRTDelta: 4.14°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.47°CMRTDelta: 3.97°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = MRT (TCI-11)solarAdjustedMRT: 5.17°CMRTDelta: 3.97°C
Thanks a lot for your helpRegards,
Aymeric
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hope this number will grow in future. Currently available features are:
1) Creation of 2d or 3d context for any kind of building related analysis: automatically generate the 2d/3d surrounding buildings for the location where you would like to perform visibility, solar radiation, cfd or any other type of analysis. You need some other plugin for the last three, like Ladybug. It only creates the context=surroundings! The "automatic generation" process also includes creation of the local topography (terrain) along with buildings.
2) Identification of certain 2d or 3d elements in the created context. For example: selection of all hotels, parks, hospitals, restaurants, residential buildings etc.
3) Performing direct terrain analysis (hillshading, slope, ruggedness, roughness, water flow...)
4) Creation of terrain shading masks and horizon files for further solar and photovoltaics analysis.
Gismo will be very grateful if he could get any suggestions, improvements, bug reports and testing in the following period. In case you are willing to provide any of these, the requirements, installation steps and .gh example files can be found here, here and here.
Thank you in advance !!…
Added by djordje to Gismo at 9:10am on January 29, 2017
Karamba.
I am using your plug-in for normal forces evaluation in the transvere wires and spreaders of a sailboat. Mast is solved in another way, so I am not taking forces from Karamba in that case.
Basing on the forces value an adequate wire size (diameter) is choosen. Then masses of wires are being calculated. Loads (forces) on longitudinal wires are calculated without Karamba. The problem is when choosing transverse wires’ mass minimization as a criteria, the Octopus doesn’t get any results - is changing the sliders (genes) too fast for Karamba to calculate the forces (so Octopus gets only nulls):
When minimization of a e.g. longitudinal wires’ mass (calculated without Karamba) is taken as a criteria Octopus works fine.
Which suggests that the problem is in interaction of two plug-ins.
Any ideas how to avoid that problem?
Thanks,
M.
Below some screenshots of definition part with Karamba:
1675×807 200 K
image.png1680×789 398 KB
Despite the ‘orange warning’ the values are correct (double checked with other software).However I don't know why does it say that there is a part that can move freely without deformation,as the model looks like this:
image.png1239×343 55.5 KB
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t defined from the discussion of radiation exchange between urban surfaces and the sky in urban heat island research (See Oke's literature list below). It will be affected by the proportion of sky visible from a given calculation point on a surface (vertical or horizontal) as a result of the obstruction of urban geometry, but it is not entirely associated with the solid angle subtended by the visible sky patch/patches.
So, I think using "geometry way" to approximate Sky View Factor is not correct. Sky View Factor calculation shall be based on the first principle defining the concept: radiation exchange between urban surface and sky hemisphere:
(image extracted from Johnson, G. T., & Watson, 1984)
Therefore, I always refer to the following "theoretical" Sky View Factors calculated at the centre of an infinitely long street canyon with different Height-to-width ratios in Oke's original paper (1981) as the ultimate benchmark to validate different methods to calculate SVF:
So, I agree with Compagnon (2004) on the method he used to calculate SVF: a simple radiation (or illuminance) simulation using a uniform sky.
The following images are the results of the workflow I built in the procedural modeling software Houdini (using its python library) according to this principle by calling Radiance to do the simulation and calculation, and the SVF values calculated for different canyon H/W ratios (shown at the bottom of each image) are very close to the values shown in Oke's paper.
H/W=0.25, SVF=0.895
H/W=1, SVF=0.447
H/W=2, SVF=0.246
It seems that the Sky View Factor calculated from the viewAnalysis component in Ladybug is not aligned with Oke's result for a given H/W ration: (GH file attached)
According to the definition shown in this component, I assume the value calculated is the percentage of visible sky which is a geometric calculation (shooting evenly distributed rays from sensor point to the sky and calculate the ratio of rays not blocked by urban geometry?), i.e solid angle subtended by visible sky patches, and it is not aligned with the original radiation exchange definition of Sky View Factor.
I'd suggest to call this geometrically calculated ratio of visible sky "Sky Exposure Factor" which is "true" to its definition and way of calculation (see the paper on Sky Exposure Factor below) so as to avoid confusion with "The Sky View Factor based on radiation exchange" as discussed in urban climate literature.
Appreciate your comments and advice!
References:
SVF: definition based on first principle
Oke, T. R. (1981). Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations. Journal of Climatology, 1(3), 237-254.
Oke, T. R. (1987). Boundary layer climates (2nd ed.). London ; New York: Methuen.
Johnson, G. T., & Watson, I. D. (1984). The Determination of View-Factors in Urban Canyons. Journal of American Meteorological Society, 23, 329-335.
Watson, I. D., & Johnson, G. T. (1987). Graphical estimation of sky view-factors in urban environments. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 7(2), 193-197. doi: 10.1002/joc.3370070210
Papers on SVF calculation:
Brown, M. J., Grimmond, S., & Ratti, C. (2001). Comparison of Methodologies for Computing Sky View Factor in Urban Environments. Los Alamos, New Mexico, USA: Los Alamos National Laboratory.
SVF calculation based on first principle:
Compagnon, R. (2004). Solar and daylight availability in the urban fabric. Energy and Buildings, 36(4), 321-328.
paper on Sky Exposure Factor:
Zhang, J., Heng, C. K., Malone-Lee, L. C., Hii, D. J. C., Janssen, P., Leung, K. S., & Tan, B. K. (2012). Evaluating environmental implications of density: A comparative case study on the relationship between density, urban block typology and sky exposure. Automation in Construction, 22, 90-101. doi: 10.1016/j.autcon.2011.06.011
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eather data so it cannot be easily compared to Archsim. My account of the differences between Honeybee and Archsim will be far from complete but here are the key ones that I am aware of:
1) This difference is a bit of a superficial one but points to a deeper thinking about how the software should be used. Honeybee has many more components than Archsim, which means that Honeybee has a steeper learning curve than Archsim and will take longer to master. Along with this, you may also encounter a general mentality in the Honeybee community that "you should not be running a certain type of simulation unless you know how it works" whereas I know that Archsim is a bit more amenable to making things fast and easy to set up even when you are not sure what is going on under the hood. However, as a result of the large number of components in Honeybee, it is more open-ended, customizable, and includes more freedom in terms of cases that you can run and the parameters of the energy simulation that you can change than Archsim. You will also notice that, while there is a general ethos in the Honeybee community that you should not be running certain simulations unless you know what you are doing, we try to provide you with many resources to educate yourself if you are motivated. For example, we have long component descriptions that we assemble into documentation books like this (https://www.gitbook.com/book/mostapharoudsari/honeybee-primer/details), hours of video tutorial playlist like this one (https://www.youtube.com/playlist?list=PLruLh1AdY-SgW4uDtNSMLeiUmA8YXEHT_), and many GH example files on a github-based file sharing system (https://hydrashare.github.io/hydra/index.html). Not to mention a community of people who would respond to discussions like this one.
2) Archsim as a standalone application will soon be no more and will be instead distributed with the DIVA daylight analysis tool (http://diva4rhino.com/). While I am unclear on the exact trajectory of DIVA, it currently has a price tag attached to it and so I would assume that the future of Archsim will also carry this price tag. On the other hand, Honeybee and any derivative software will forever be free and open source under the GPL licence (https://github.com/mostaphaRoudsari/Honeybee/blob/master/License_Honeybee_GPL.txt).
3) This third point is a bit of a reiteration of the last one but Honeybee is open source, meaning that, if you need a feature of EnergyPlus that is not yet implemented on either interface, you can usually add it in yourself with a few lines of python code in Honeybee. This type of workflow is not possible with Archsim since it is closed source and requires you to use EnergyPlus's text editor interface after Archsim has exported an IDF in order to implement any additional EnerygPlus features.
4) The libraries and templates for Honeybee come from OpenStudio - the open source interface for EnergyPlus (https://www.openstudio.net/), which is supported by the US Department of Energy (just like EnergyPlus). Since Honeybee is open source, it is able to make use of the large database of building type schedules/loads and constructions that have been assembled by the OpenStudio team over the last several years as well as OpenStudio's SDK. I can also say that almost all of the development efforts of the Honeybee team are now focused now on integrating efforts with OpenStudio, including an exporter from Honeybee to OpenStudio that should be fully functional for the next stable release. I am not certain of the current extent of Archsim's libraries but, last I had checked, the creator was pulling them from his own experience and, as such, only had a few libraries to choose from. For all of my knowledge, through, this may be changing with the integration of Archsim with DIVA.
Let me know if this is helpful and, if anyone has more up-to-date knowledge on Archsim than I, please post there.
-Chris…
er). With the command "End Bulge" I noticed that G2 moves perpendicular to G1! But with an increase which is not equal... and is different, every time, depending on the angle between G0 and G1 and G2. How do I predict the position of G2 compared to G1 simulating the "End Bulge" command? Thank you for your professional answers.
^___^
Below you can see an example with a curve crimson ... If I move G1 of 1 unit G2 moves of 0.42 units (perpendicular) .. If I move of 2 units the next step is 0.46 unit... 3 units --> step 0,50 units... etc.
And each time changes depending on the initial conditions (G0/G1/G2 angle).
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Added by Lucius Santo at 4:21pm on September 20, 2012
or GH with: 1. Animation Timeline 2. Rendering 3. API
Summary:
Animation Timeline: Smooth animation system that plays at the real-world speed; so you know the robot will run just right when you upload the code.
Rendering: Extensive options and outputs; so you can generate amazing videos.
API: Access our functions through Python and C# scripting; so you can manage parameters and actions for complex processes for each target.
More info:
Animation Timeline:
Build an animation from a list of Planes, it's that easy! Get these from points, curves or surfaces. Download the example files with the trial and test it yourself.
The unique Timeline component displays all the important robot warnings and the digital Input/Ouput:
RED – clash detection BLUE - singularities YELLOW – over rotation ORANGE – out of reach Digital Inut/Output: red=off, green=on
Rendering:
IO smoothly interpolates between all the Planes you set. This means you can generate keyframes for positions between Planes too e.g. you have two planes defining a tool path, IO can generate 2000 keyframes. Smooooth!
Rendered in full colour as standard, not GH red :-)
LiveBaking - let's you use Rhino render settings in real-time (can be a bit slow!)
Slider animation - use the native 'Animate' option to export hi-res images and create videos easily. Just set the number of frames you need (hint: divide total time in seconds by the frames-per-second rate)
Bake unlimited meshes as keyframes for export to render-pipelines in 3DS etc.
API
Accessing the IO functions through Python and C# let's you build more powerful definitions. You can assign data to every position the robot reaches, allowing you to control speed, acceleration, wait-times, actions and more. Examples comparing C# with Python are included in the examples files.
You can also use teh API build your own plugins that use the IO timeline to do all the hard work like IK and creating valid code, while you enjoy developing your new process...
Check out the website for more features and videos of the example definitions: www.robots.io
Download the PDF guide: 150314_IO_Primer_v1.pdf.
See www.robots.io for more info and pricing.
Developed by RoboFold Ltd. Used by leading academics, researchers and professionals.
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Added by Gregory Epps at 10:15am on November 7, 2014